ABSTRACT:

Healthy sleep is important for students’ academic performance and well-being. However, many students obtain insufficient sleep and may not reach their full learning potential. In this thesis, I tested the university-wide effects of class start times and chronotype on students’ sleep and academic performance. Students’ diurnal patterns of logins on the university’s Learning Management System (LMS) were used to estimate nocturnal sleep opportunities, and to categorize students into chronotype groups (early, intermediate, late). LMS-derived sleep behavior was verified in actigraphy studies. Wi-Fi connection logs were used to estimate students’ lecture attendance. In my first study, I showed that morning classes were associated with lower lecture attendance, shorter sleep, and lower academic achievement. Therefore, universities should avoid scheduling early morning classes. In my second study, I showed that late-type students had poorer academic performance than their peers. Late-type students had shorter sleep only for morning classes, poorer well-being and metacognitive self-regulation, and lower lecture attendance. These findings suggest that multiple factors contribute to poorer learning in late-type students. My work shows that universities can use passively collected data to evaluate the impact of their practices on students’ sleep and learning. These approaches can guide interventions to improve students’ health and performance.

THESIS ADVISOR:  
A/Prof. Joshua Gooley

VENUE:
Zoom ID:
881 7212 7548

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655346